公路地基真空排水预压法探讨

真空排水预压法与堆载预压法相比具有加载快、无需堆载材料、不会失稳等优势,适用于加固软土特别是含水量较高的超软土地基。真空-堆载联合预压法的应用也越来越多。经过国内外十几年的探索,真空排水预压法日趋成熟,已经成为大面积应用的加固软土地基的行之有效的方法之一。     

Human-like autonomous car-following model with deep reinforcement learning

This study proposes a framework for human-like autonomous car-following planning based on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation environment where an RL agent learns from trial and error interactions based on a reward function that signals how much the agent deviates from the empirical data. Through these interactions, an optimal policy, or car-following model that maps in a human-like way from speed, relative speed between a lead and following vehicle, and inter-vehicle spacing to acceleration of a following vehicle is finally obtained. The model can be continuously updated when more data are fed in. Two thousand car-following periods extracted from the 2015 Shanghai Naturalistic Driving Study were used to train the model and compare its performance with that of traditional and recent data-driven car-following models. As shown by this study’s results, a deep deterministic policy gradient car-following model that uses disparity between simulated and observed speed as the reward function and considers a reaction delay of 1 s, denoted as DDPGvRT, can reproduce human-like car-following behavior with higher accuracy than traditional and recent data-driven car-following models. Specifically, the DDPGvRT model has a spacing validation error of 18% and speed validation error of 5%, which are less than those of other models, including the intelligent driver model, models based on locally weighted regression, and conventional neural network-based models. Moreover, the DDPGvRT demonstrates good capability of generalization to various driving situations and can adapt to different drivers by continuously learning. This study demonstrates that reinforcement learning methodology can offer insight into driver behavior and can contribute to the development of human-like autonomous driving algorithms and traffic-flow models.     

桥梁单板受力的原因及解决措施

随着交通量的迅猛增长,桥梁单板受力情况越来越频繁,通过对单板受力现象产生原因进行分析,提出解决措施,以供同行参考和借鉴。     

浅埋顶管沉井周边土体的三维破坏形状及沉降研究

为研究顶管沉井及周边土体在顶进力作用下的形变范围与大小，以加固旋喷桩作为沉井周围加固体建立ABAQUS软件计算模型，并将模拟结果与工程实例、PLAXIS 3D软件所得结果进行对比分析。同时，采用广州地区花岗岩残积土进行室内沉井模型试验，并通过试验结果对数值模拟结论进行验证，得出结论如下： 1）在开挖基坑前达到设计强度的旋喷桩能有效减小基坑周边土体塌陷变形、坑底隆起。2）在施加工作顶推力下，前侧主动区首先出现贯通裂缝，竖向位移斜率增大出现明显拐点；继续增大顶推力，土体位移会急剧增大导致地表沉降严重。3）对于后背土体，在顶推力作用下，地表破裂线的切线角度从0°逐渐增大至45°+φ/2，导致破裂范围也不断扩大；达到45°+φ/2处后，继续施加顶推力会导致短轴方向破坏范围扩大的速度较长轴方向的速度更快；三维空间中被动区破坏土体在地表处产生形状为椭圆的破坏面，椭圆长轴方向为顶推轴线方向，被动破坏体呈现为牛角状椭圆楔体。     

Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditions北大核心CSCD

［Objective ］ To meet the requirements of remotely controlling ship in curved, narrow and crowded inland waterways, this paper proposes an approach that consists of CNN-based algorithms and knowledge based models under ship-shore cooperation conditions. ［Method］On the basis of analyzing the characteristics of ship-shore cooperation, the proposed approach realizes autonomous perception of the environment with visual simulation at the core and navigation decision-making control based on deep reinforcement learning, and finally constructs an artificial intelligence system composed of image deep learning processing, navigation situation cognition, route steady-state control and other functions. Remote control and short-time autonomous navigation of operating ships are realized under inland waterway conditions, and remote control of container ships and ferries is carried out. ［Results］The proposed approach is capable of replacing manual work by remote orders or independent decision-making, as well as realizing independent obstacle avoidance, with a consistent deviation of less than 20 meters. ［Conclusions］The developed prototype system carries out the remote control operation demonstration of the above ship types in such waterways as the Changhu Canal Shenzhou line and the Yangtze River, proving that a complete set of algorithms with a CNN and reinforcement learning at the core can independently extract key navigation information, construct obstacle avoidance and control awareness, and lay the foundation for inland river intelligent navigation systems. © 2022 Journal of Clinical Hepatology. All rights reserved.     

浅析G30线K3981～K3982路段防沙害处治方法

结合博乐公路管理局管养的G30线K3981～K3982路段路基边坡防沙害处治养护项目的实施，对处治沙害实施流程进行了详细的阐述，有一定的参考价值。     

汕头苏埃隧道方案设计关键技术研究

根据汕头苏埃隧道的建设条件,对工程方案设计中的几个技术难点进行研究,并提出解决方案。通过采用"多级分流"理念,实现隧道与北岸4条城市主干道的交通衔接;选择"抛石+排水板"方案解决海域深厚淤泥地层中的围堰设计;8度高烈度震区选择合理的抗震减震措施解决隧道结构抗震;采取双道密封垫和加大密封垫断面的防水设计,满足地震时管片接缝张开量大的防水要求;针对复杂地层,对盾构选型和配置提出建议;对海底凸起进入隧道内的硬岩进行爆破预处理,以降低盾构施工风险。     

105国道新丰段加铺水泥砼路面改造探讨

以105国道新丰段路面大修工程为依据,通过对旧路面的调查,分析了水泥砼路面损坏的原因,并采用了对应的处治措施。     

探讨沥青路面局部渗水的原因及处理方法

通过武汉市汉蔡高速公路沥青路面出现的局部渗水现象,分析沥青路面产生局部渗水的原因及处理的必要性,提出对沥青路面局部渗水的处理原则及处理方法。     

京珠高速公路隧道病害检测与处治对策研究

通过京珠高速公路隧道病害现场检测,对其主要病害进行了分类统计。考虑该隧道的勘察、设计、施工等因素影响,对该隧道主要病害产生原因进行了分析,在此基础上,对隧道病害等级进行了判定,并针对不同等级病害,提出了具体的处治措施。